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Confidence Cycles and Liquidity Hoarding

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  • Volha Audzei

    (Czech National Bank)

Abstract

Market confidence has proved to be an important factor during past economic crises. In this paper, I incorporate a model of the interbank market into a DSGE model, with the volume of lending depending on market confidence. I conduct an exercise to mimic some central bank policies: provision of liquidity and reduction of the reserve rate. My results indicate that policy actions have a limited effect on the supply of credit if they fail to influence agents' expectations. A low reserve rate policy worsens recessions due to its negative impacts on bank revenues.

Suggested Citation

  • Volha Audzei, 2022. "Confidence Cycles and Liquidity Hoarding," International Journal of Central Banking, International Journal of Central Banking, vol. 18(3), pages 281-320, September.
    • Handle: RePEc:ijc:ijcjou:y:2022:q:3:a:7
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    References listed on IDEAS

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    1. Clark, Todd E. & Davig, Troy, 2011. "Decomposing the declining volatility of long-term inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 35(7), pages 981-999, July.
    2. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    3. Heider, F. & Hoerova, M. & Holthausen, C., 2009. "Liquidity Hoarding and Interbank Market Spreads : The Role of Counterparty Risk," Discussion Paper 2009-40 S, Tilburg University, Center for Economic Research.
    4. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    5. Carlos Capistr¡N & Allan Timmermann, 2009. "Disagreement and Biases in Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(2-3), pages 365-396, March.
    6. Siklos, Pierre L., 2013. "Sources of disagreement in inflation forecasts: An international empirical investigation," Journal of International Economics, Elsevier, vol. 90(1), pages 218-231.
    7. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    8. Pfajfar, Damjan, 2013. "Formation of rationally heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1434-1452.
    9. Gertler, Mark & Kiyotaki, Nobuhiro, 2010. "Financial Intermediation and Credit Policy in Business Cycle Analysis," Handbook of Monetary Economics, in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 11, pages 547-599, Elsevier.
    10. Cúrdia, Vasco & Woodford, Michael, 2011. "The central-bank balance sheet as an instrument of monetarypolicy," Journal of Monetary Economics, Elsevier, vol. 58(1), pages 54-79, January.
    11. Hommes, Cars, 2011. "The heterogeneous expectations hypothesis: Some evidence from the lab," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 1-24, January.
    12. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    13. Kim, Don H. & Orphanides, Athanasios, 2012. "Term Structure Estimation with Survey Data on Interest Rate Forecasts," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(1), pages 241-272, February.
    14. Fildes, Robert & Goodwin, Paul & Lawrence, Michael & Nikolopoulos, Konstantinos, 2009. "Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning," International Journal of Forecasting, Elsevier, vol. 25(1), pages 3-23.
    15. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    16. Allen, Franklin & Carletti, Elena & Gale, Douglas, 2009. "Interbank market liquidity and central bank intervention," Journal of Monetary Economics, Elsevier, vol. 56(5), pages 639-652, July.
    17. Hilberg, Björn & Hollmayr, Josef, 2011. "Asset prices, collateral and unconventional monetary policy in a DSGE model," Working Paper Series 1373, European Central Bank.
    18. Franses, Philip Hans & Kranendonk, Henk C. & Lanser, Debby, 2011. "One model and various experts: Evaluating Dutch macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 482-495.
    19. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.
    20. Volha Audzei, 2012. "Efficiency of Central Bank Policy During the Crisis : Role of Expectations in Reinforcing Hoarding Behavior," CERGE-EI Working Papers wp477, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    21. Paul Beaudry & Deokwoo Nam & Jian Wang, 2011. "Do Mood Swings Drive Business Cycles and is it Rational?," NBER Working Papers 17651, National Bureau of Economic Research, Inc.
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    1. Confidence Cycles and Liquidity Hoarding
      by Christian Zimmermann in NEP-DGE blog on 2016-11-16 21:00:22

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    More about this item

    JEL classification:

    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • E65 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Studies of Particular Policy Episodes
    • E71 - Macroeconomics and Monetary Economics - - Macro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on the Macro Economy
    • G01 - Financial Economics - - General - - - Financial Crises

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